Maybe this can help.
https://stackoverflow.com/questions/32959723/set-python-path-for-spark-worker
On 04/10/2018 12:19 μμ, Jianshi Huang wrote:
Hi,
I have a problem using multiple versions of Pyspark on YARN, the
driver and worker nodes are all preinstalled with Spark 2.2.1, for
production tasks. And I want to use 2.3.2 for my personal EDA.
I've tried both 'pyFiles=' option and sparkContext.addPyFiles(),
however on the worker node, the PYTHONPATH still uses the system
SPARK_HOME.
Anyone knows how to override the PYTHONPATH on worker nodes?
Here's the error message,
Py4JJavaError: An error occurred while calling o75.collectToPython.
: org.apache.spark.SparkException: Job aborted due to stage
failure: Task 0 in stage 0.0 failed 4 times, most recent failure:
Lost task 0.3 in stage 0.0 (TID 3, emr-worker-8.cluster-68492,
executor 2): org.apache.spark.SparkException:
Error from python worker:
Traceback (most recent call last):
File "/usr/local/Python-3.6.4/lib/python3.6/runpy.py", line 183,
in _run_module_as_main
mod_name, mod_spec, code = _get_module_details(mod_name, _Error)
File "/usr/local/Python-3.6.4/lib/python3.6/runpy.py", line 109,
in _get_module_details
__import__(pkg_name)
File
"/usr/lib/spark-current/python/lib/pyspark.zip/pyspark/__init__.py",
line 46, in <module>
File
"/usr/lib/spark-current/python/lib/pyspark.zip/pyspark/context.py",
line 29, in <module>
ModuleNotFoundError: No module named 'py4j'
PYTHONPATH was:
/usr/lib/spark-current/python/lib/pyspark.zip:/usr/lib/spark-current/python/lib/py4j-0.10.7-src.zip:/mnt/disk1/yarn/usercache/jianshi.huang/filecache/130/__spark_libs__5227988272944669714.zip/spark-core_2.11-2.3.2.jar
And here's how I started Pyspark session in Jupyter.
%env SPARK_HOME=/opt/apps/ecm/service/spark/2.3.2-bin-hadoop2.7
%env PYSPARK_PYTHON=/usr/bin/python3
import findspark
findspark.init()
import pyspark
sparkConf = pyspark.SparkConf()
sparkConf.setAll([
('spark.cores.max', '96')
,('spark.driver.memory', '2g')
,('spark.executor.cores', '4')
,('spark.executor.instances', '2')
,('spark.executor.memory', '4g')
,('spark.network.timeout', '800')
,('spark.scheduler.mode', 'FAIR')
,('spark.shuffle.service.enabled', 'true')
,('spark.dynamicAllocation.enabled', 'true')
])
py_files =
['hdfs://emr-header-1.cluster-68492:9000/lib/py4j-0.10.7-src.zip']
sc = pyspark.SparkContext(appName="Jianshi", master="yarn-client",
conf=sparkConf, pyFiles=py_files)
Thanks,
--
Jianshi Huang
--
Apostolos N. Papadopoulos, Associate Professor
Department of Informatics
Aristotle University of Thessaloniki
Thessaloniki, GREECE
tel: ++0030312310991918
email: papad...@csd.auth.gr
twitter: @papadopoulos_ap
web: http://datalab.csd.auth.gr/~apostol
